Senior Engineer responsible for building and operating the Enterprise Core Platform (ECP) control plane on Azure, driving platform modernization, AI-native capabilities, and platform-as-a-product practices.
Locations (5)
Seattle, Washington, United States
Downtown Seattle, Washington, United States
Federal Way, Washington, United States
Lynnwood, Washington, United States
Bellevue, Washington, United States
Compensation
Base Salary: $142,000 - $214,000
Responsibilities
Build and operate the Go control plane and its providers
Own capabilities end-to-end from design to operational support
Modernize Azure Kubernetes Service, GitOps, infrastructure as code
Lead migrations and define platform ownership
Communicate technical decisions via ADRs and design notes
Own the data layer that makes CX work, design analysis and measurement frameworks, build and scale reporting pipelines, and partner with cross‑functional teams to drive data‑driven CX strategy.
Locations (2)
Denver, Colorado, United States
New York, New York, United States
Compensation
Our cash compensation amount for this role is $132,210/yr to $165,263/yr in Denver, $160,000/yr to $200,000/yr for New York. Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above.
Responsibilities
Own ambiguous problems, design analysis and measurement frameworks, and introduce policies and practices by which data integrity is monitored and enforced within your domain.
Deliver multiple high‑impact projects, balancing trade‑offs to maximize business value, and maintain clear expectations of deliverables and timelines.
Partner with CX leaders, cross‑function data‑science teams, tool developers (e.g. Salesforce), and data engineering to align on strategy.
Apply advanced statistical methods and AI‑driven anomaly detection to proactively uncover opportunities, diagnose performance issues, and shape CX strategy.
AI Agent Orchestration Engineer responsible for designing, building, and scaling graph-based AI agents and tools within Majesco’s AI-native platform.
Responsibilities
Design and implement typed agent state, schemas, data contracts, and validation using Python and Pydantic
Build LangChain and LangGraph workflows with conditional branching, parallel task execution, retries, sub-agents, checkpoints, and human-in-the-loop approvals
Develop and extend Majesco AI Core integrations using GraphExecutor, ExecutorFactory, ToolResolver, Agent Registry, Tool Registry, and MajescoCheckpointer
Design and implement reusable asynchronous tools, including API integrations, authentication, request/response handling, error recovery, registration, and database metadata
Create reliable graph-agent execution patterns that support modularity, testability, observability, and operational resilience
Requirements
Bachelor’s or master’s degree in Computer Science, Engineering, Information Technology, or a related discipline
Senior Software Engineer responsible for designing, building, and scaling the core backend systems and microservices that power the freight and LTL carrier network.
Responsibilities
Own the core applications and algorithms that power freight and LTL carrier network
Design, build, and ship critical backend systems for carrier profiles, fleet management, schedules, and onboarding workflows
Architect marketplace mechanics for automated dispatch, matching shipments to carriers, scoring assignments, and managing offer expirations
Integrate routing, pricing, and payout rules to ensure on-time shipments and accurate financial pipelines
Debug production issues, ship API endpoints and database migrations, and operate background jobs and event‑streaming workflows
Senior Software Engineer responsible for designing, building, and evolving cloud‑native platforms using AWS serverless technologies and MongoDB.
Responsibilities
Owning the design and delivery of high‑quality software solutions, working end‑to‑end across features, services, and systems to deliver meaningful customer and business outcomes
Building and operating cloud‑native, serverless applications on AWS, ensuring solutions are secure, resilient, scalable, and optimised for performance and cost
Leading by example in applying clean code, sound architectural principles, and engineering best practices that align with Legal & General’s SSDLC and technology strategy
Actively identifying, prioritising, and addressing technical debt, ensuring long‑term maintainability, reliability, and operability of our platforms
Defining and influencing test strategies that raise the quality bar, with a strong focus on security, accessibility, usability, resilience, and non‑functional requirements
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